Manta Ray Foraging Optimization with Quasi-reflected Opposition Strategy for Global Optimization-Reference-Cited by-同舟云学术

Manta Ray Foraging Optimization with Quasi-reflected Opposition Strategy for Global Optimization

Published:2022 Issue: Volume: Page:477-485
ISSN:1876-1100
Container-title:Lecture Notes in Electrical Engineering
language:
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Author:

Abdul Razak Ahmad Azwan,Nasir Ahmad Nor Kasruddin,Abdul Ghani Nor Maniha,Mat Jusof Mohd Falfazli

Publisher

Springer Singapore

Link

https://link.springer.com/content/pdf/10.1007/978-981-16-8690-0_43

Reference19 articles.

1. Zhao W, Zhenxing Z, Liying W (2020) Manta ray foraging optimization: an effective bio-inspired optimizer for engineering applications. Eng. Appl. Artif. Intell. 87:10330

2. Armstrong AJ, et al (2019) The geographic distribution of reef and oceanic manta rays in the south-east Indian and south-west Pacific Oceans. BioRxiv, 727651

3. El-Hameed MA, Elkholy MM, El-Fergany AA (2020) Three-diode model for characterization of industrial solar generating units using Manta-rays foraging optimizer: analysis and validations. Energy Conv. Manag 219:113048. https://doi.org/10.1016/j.enconman.2020.113048

4. Ghosh KK, Guha R, Bera SK, Kumar N, Sarkar R (2021) S-shaped versus V-shaped transfer functions for binary Manta ray foraging optimization in feature selection problem. Neural Comput Appl 33(17):11027–11041. https://doi.org/10.1007/s00521-020-05560-9

5. Rohner CA, Katherine BB, Joshua MR, Stewart D, Ponzo A, Anthony JR (2017) Mobulid rays feed on euphausiids in the Bohol Sea. Roy. Soc. Open Sci. 4(5):161060

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